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Abstract

Three-dimensional (3D) object tomography from a two-dimensional recorded hologram
is a process of high-dimensional data inference from undersampled data. As such,
recently, techniques developed in the field of compressive sensing and sparse
representation have been applied for this task. While many applications of
compressive sensing for tomography from digital holograms have been demonstrated
in the past few years, the fundamental limits involved have not yet been
addressed. We formulate the guarantees for compressive sensing-based recovery of
3D objects and show their relation to the physical attributes of the recording
setup.

References

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